Left Right Judgement Task and Sensory, Motor, and Cognitive Assessment in Participants with Wrist/Hand Pain
Bibliographic record
Abstract
The Left Right Judgement Task (LRJT) involves determining if an image of the body part is of the left or right side. The LRJT has been utilized as part of rehabilitation treatment programs for persons with pain associated with musculoskeletal injuries and conditions. Although studies often attribute changes and improvement in LRJT performance to an altered body schema, imaging studies suggest that the LRJT implicates other cortical regions. We hypothesized that cognitive factors would be related to LRJT performance of hands and feet and that sensory, motor, and pain related factors would be related to LRJT in the affected hand of participants with wrist/hand pain. In an observational cross-sectional study, sixty-one participants with wrist/hand pain participated in a study assessing motor imagery ability, cognitive (Stroop test), sensory (Two-Point Orientation Discrimination, pressure pain thresholds), motor (grip strength, Purdue Pegboard Test), and pain related measures (West Haven Yale Multidimensional Pain Inventory) as well as disability (Disability of the Arm, Shoulder and Hand). Multiple linear regression found Stroop test time and motor imagery ability to be related to LRJT performance. Tactile acuity, motor performance, participation in general activities, and the taking of pain medications were predictors of LRJT accuracy in the affected hand. Participants who took pain medications performed poorly in both LRJT accuracy (p=0.001) and reaction time of the affected hand (p=0.009). These participants had poorer cognitive (p=0.013) and motor function (p=0.002), and higher pain severity scores (p=0.010). The results suggest that the LRJT is a complex mental task that involves cognitive, sensory, motor, and behavioural processes. Differences between persons with and without pain and improvement in LRJT performance may be attributed to any of these factors and should be considered in rehabilitation research and practice utilizing this task.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".